Using Yolo9000

Using Yolo9000

Simultaneous detection and classification of 9000 objects: darknet.exe detector test cfg/combine9k.data cfg/yolo9000.cfg yolo9000.weights data/dog.jpg

• yolo9000.weights - (186 MB Yolo9000 Model) requires 4 GB GPU-RAM: http://pjreddie.com/media/files/yolo9000.weights

• yolo9000.cfg - cfg-file of the Yolo9000, also there are paths to the 9k.tree and coco9k.map https://github.com/AlexeyAB/darknet/blob/617cf313ccb1fe005db3f7d88dec04a04bd97cc2/cfg/yolo9000.cfg#L217-L218

  • 9k.tree - WordTree of 9418 categories - <label> <parent_it>, if parent_id == -1 then this label hasn't parent: https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/9k.tree

  • coco9k.map - map 80 categories from MSCOCO to WordTree 9k.tree: https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/coco9k.map

• combine9k.data - data file, there are paths to: 9k.labels, 9k.names, inet9k.map, (change path to your combine9k.train.list): https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/combine9k.data

  • 9k.labels - 9418 labels of objects: https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/9k.labels

  • 9k.names - 9418 names of objects: https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/9k.names

  • inet9k.map - map 200 categories from ImageNet to WordTree 9k.tree: https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/inet9k.map